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Antialiased super-resolution with parallel high-frequency synthesis

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Abstract

Image super-resolution (SR) increases the resolution of the target image, and has become a fundamental image-editing operation for real-world applications. Traditional methods often cause jaggies and blurring artifacts because natural images generally contain a lot of discrete continuities and edges. This paper proposes a new synthesis-based method for image super-resolution at a pixel level that takes advantages of convolution-based edge anti-aliasing. The target images are divided into two components representing, respectively, the high- and low-frequency contents of the images. We perform bicubic interpolation to reconstruct the missing information in the low-frequency component. A patch-based texture synthesis is subsequently adopted to synthesize the high-frequency patches with the final upscaled images. In particular, we also use the efficient edge-based anti-aliasing for correcting the quantization error, restore the high-frequency details damaged by nonlinear example-based synthesis. Our proposed approach generates super-resolution images dynamically and can be fully implemented in GPU parallelization. Experiments confirm the visual superiority of our proposed approach in comparison with competing state-of-the-art techniques.

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Acknowledgments

The authors would like to thank all reviewers for their helpful suggestions and constructive comments. The work is supported by the National Natural Science Foundation of China (No.61202154, 61572316, 61272326, 61133009), the National Basic Research Project of China (No. 2011CB302203), National High-tech R&D Program of China (863 Program)(Grant No. 2015AA011604), and Shanghai Pujiang Program (No.13PJ1404500), the Science and Technology Commission of Shanghai Municipality Program (No. 13511505000), the Open Projects Program of National Laboratory of Pattern Recognition, and the Open Project Program of the State Key Lab of CAD&CG (Grant No. A1401), Zhejiang University.

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Correspondence to Bin Sheng.

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Jiang, X., Sheng, B., Lin, W. et al. Antialiased super-resolution with parallel high-frequency synthesis. Multimed Tools Appl 76, 543–560 (2017). https://doi.org/10.1007/s11042-015-3049-8

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  • DOI: https://doi.org/10.1007/s11042-015-3049-8

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